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Journal articles on the topic 'Economics, Mathematical'

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Published: 4 June 2021
Last updated: 30 July 2024

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1

Tarasov, Vasily E. "Mathematical Economics: Application of Fractional Calculus." Mathematics 8, no. 5 (April 27, 2020): 660. http://dx.doi.org/10.3390/math8050660.

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2

Becker, Robert A., and Stanley Reiter. "Studies in Mathematical Economics." American Mathematical Monthly 95, no. 3 (March 1988): 268. http://dx.doi.org/10.2307/2323639.

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3

Pemberton, Malcolm, and Frederick Van Der Ploeg. "Mathematical Methods in Economics." Economic Journal 95, no. 380 (December 1985): 1112. http://dx.doi.org/10.2307/2233280.

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4

Beaumont, John R., and F. Van Der Ploeg. "Mathematical Methods in Economics." Journal of the Operational Research Society 36, no. 7 (July 1985): 653. http://dx.doi.org/10.2307/2582491.

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5

Majumdar, Mukul, and Norman Schofield. "Mathematical Methods in Economics." Journal of Business & Economic Statistics 4, no. 2 (April 1986): 276. http://dx.doi.org/10.2307/1391329.

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6

Manning, Alan, and Frederick van der Ploeg. "Mathematical Methods in Economics." Economica 54, no. 214 (May 1987): 265. http://dx.doi.org/10.2307/2554405.

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7

Miller, Edward M. "Equivocation in Mathematical Economics." American Economist 37, no. 2 (October 1993): 62–67. http://dx.doi.org/10.1177/056943459303700211.

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Correct mathematical reasoning requires each word (or symbol) to have only one meaning. Because mathematical symbols do not carry with them associated definitions, the error of equivocation is easy to make. “Money” is used with multiple meanings in the standard textbook IS/LM apparatus, and in discussions of the Keynesian paradox of saving, and liquidity trap. Typically, no definition of money is consistent with both a fixed quantity of money and the holding of money for the speculative motive. Such errors can, and should be avoided by explicitly defining terms and stating which units are being used.
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8

Beaumont, John R. "Mathematical Methods in Economics." Journal of the Operational Research Society 36, no. 7 (July 1985): 653–54. http://dx.doi.org/10.1057/jors.1985.117.

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9

Guerrini, Luca. "Mathematical modeling in economics." Physics of Life Reviews 9, no. 4 (December 2012): 415–17. http://dx.doi.org/10.1016/j.plrev.2012.08.005.

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10

Tremayne, A. R., and F. van der Ploeg. "Mathematical Methods in Economics." Journal of the Royal Statistical Society. Series A (General) 148, no. 4 (1985): 395. http://dx.doi.org/10.2307/2981913.

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11

Ennuste, Ü. "TOWARDS STOCHASTIC MATHEMATICAL ECONOMICS." Proceedings of the Estonian Academy of Sciences. Humanities and Social Sciences 35, no. 2 (1986): 129. http://dx.doi.org/10.3176/hum.soc.sci.1986.2.03.

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12

Raju, Swati. "Mathematical Economics: A Mathematical Approach To Microeconomic Theory." Journal of Quantitative Economics 3, no. 1 (January 2005): 167–70. http://dx.doi.org/10.1007/bf03404783.

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13

Kurniawati, Annisa Dwi. "Sharia economics students’ anxiety towards mathematical economics course." International Journal on Teaching and Learning Mathematics 2, no. 1 (June 29, 2019): 21. http://dx.doi.org/10.18860/ijtlm.v2i1.8306.

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<p class="ABS-C">Mathematical economics is one of the compulsory courses in sharia economics students. At each exam of the mathematical economics course, the majority of scores earned by students tend to be low. It is the anxiety of facing the exam on mathematical economics courses that are considered as one of the causes. This type of research is qualitative descriptive research. The study aims to find out anxiety students have on the course of mathematical economics. The research subject is sharia economics students of IAIN Ponorogo who is taking a course in mathematical economics. The triangulation techniques of interviews, observations, and documentation are done for data retrieval. The results showed that student anxiety towards mathematical economics courses tends to be high. Some reasons for students' anxiety are educational backgrounds that are social majors, anxiety on low test scores, anxiety on the character of the lecturer, and anxiety caused by low self-efficacy in the ability to solve mathematical economics problems. From the results of this research, the lecturer is expected to be a motivator and mediator for students to reduce students' anxiety towards the courses of mathematical economics.</p>
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14

Yu, Shurui. "Research on the Mathematical Application in Economics." Advances in Economics, Management and Political Sciences 16, no. 1 (September 13, 2023): 194–99. http://dx.doi.org/10.54254/2754-1169/16/20231006.

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In the field of economics, the research and description of the basic laws of economic operation and economic phenomena should be fully combined with the current relevant mathematical ideas and methods to ensure the standardization and scientificity of the entire economic operation. Mathematics belongs to an important theoretical discipline, which is abstract and logical, and also belongs to a strong tool discipline. Through the analysis of mathematical learning and the actual attributes of economics, we should use certain mathematical methods to carry out quantitative and qualitative analysis on the knowledge points of the whole economy, so as to provide important tool resources for the development of economics. At present, mathematics has become an important part of life, and the relationship between mathematics and the economy is becoming more and more close. In real life, many economic problems need to be solved with mathematical knowledge. This paper summarizes the important role of numbers in economics, and analyzes their specific applications, so that we can have a deeper understanding of mathematical knowledge. In the field of economics, the research and description of the basic laws of economic operation and economic phenomena should be fully combined with the current relevant mathematical ideas and methods to ensure the standardization and scientificity of the entire economic operation. Mathematics belongs to an important theoretical discipline, which is abstract and logical, and also belongs to a strong tool discipline.
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15

Abduvahobovich, Nazarov Xolmòmin. "MATHEMATICS FOR ECONOMISTS: THE ESSENTIAL TOOLBOX." International Journal of Pedagogics 4, no. 6 (June 1, 2024): 51–55. http://dx.doi.org/10.37547/ijp/volume04issue06-08.

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Mathematics serves as a cornerstone for the field of economics, providing the essential tools for modeling, analyzing, and solving economic problems. This article delves into the importance of mathematics in economics, exploring key mathematical concepts and methods used by economists to understand and predict economic phenomena. By highlighting the interplay between mathematics and economics, we underscore the necessity of a robust mathematical foundation for both theoretical and applied economic analysis.
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16

KINSELLA, STEPHEN. "BLUEPRINT FOR AN ALGORITHMIC ECONOMICS." New Mathematics and Natural Computation 08, no. 01 (March 2012): 101–11. http://dx.doi.org/10.1142/s1793005712400066.

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Algorithmic economics helps us stipulate, formulate, and resolve economic problems in a more precise manner than mainstream mathematical economics. It does so by aligning theorizing about an economic problem with both the data generated by the real world and the computers used to manipulate that data. Theoretically coherent, numerically meaningful, and therefore policy relevant, answers to economic problems can be extrapolated more readily using algorithmic economics than present day mathematical economics. An algorithmic economics would allow mathematical economics to prove theorems relating to economic problems, such as the existence of equilibria defined on some metric space, with embedded mechanisms for getting to the equilibria of these problems. A blueprint for such an economics is given and discussed with an example.
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17

Jagathesan, Dr T. "A critical study of the evolution of Mathematics in Economic Analysis." JOURNAL OF DEVELOPMENT ECONOMICS AND MANAGEMENT RESEARCH STUDIES 08, no. 08 (2021): 78–82. http://dx.doi.org/10.53422/jdms.2021.8801.

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Mathematical economics is an electrifying division of study in economics. It is helpful in model building and provides mathematical form of a descriptive theory in a simple as well as easily understandable way. Economics axiomatization can be embedded with mathematical formula to make it more scientific. Some of the concepts and theories like input-output analysis, linear programming, theory of games and economic behaviour, economic problems of optimum allocation of resources, organizing and planning of production, hyper formalistic methods now the application of computer simulation, normative economics ideas into positive economics for testing its validity given the normative assumptions, and failure of some mathematical models. This paper discusses about the evolution of mathematical economics critically.
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18

Larson, B. "Early Developments in Mathematical Economics." History of Political Economy 17, no. 2 (June 1, 1985): 324–25. http://dx.doi.org/10.1215/00182702-17-2-324.

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19

Birner, Jack. "Neoclassical Economics as Mathematical Metaphysics." History of Political Economy 25, suppl_1 (January 1, 1993): 83–117. http://dx.doi.org/10.1215/00182702-1993-suppl_1013.

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20

Yoshida, Hiroyuki. "Chaotic fluctuations in mathematical economics." Journal of Physics: Conference Series 285 (March 1, 2011): 012021. http://dx.doi.org/10.1088/1742-6596/285/1/012021.

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21

Brauers, Willem K. "Interpreting mathematical economics and econometrics." Long Range Planning 19, no. 1 (February 1986): 131. http://dx.doi.org/10.1016/0024-6301(86)90141-x.

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22

Vela Velupillai, K. "Sraffa's mathematical economics: aconstructive1 interpretation." Journal of Economic Methodology 15, no. 4 (December 2008): 325–42. http://dx.doi.org/10.1080/13501780802112858.

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23

Ponsard, Claude. "Fuzzy mathematical models in economics." Fuzzy Sets and Systems 28, no. 3 (December 1988): 273–83. http://dx.doi.org/10.1016/0165-0114(88)90034-6.

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24

MILNER, B. "Mathematical economics in Soviet management." Omega 16, no. 3 (1988): 203–5. http://dx.doi.org/10.1016/0305-0483(88)90054-0.

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25

Tarasov, Vasily. "On History of Mathematical Economics: Application of Fractional Calculus." Mathematics 7, no. 6 (June 4, 2019): 509. http://dx.doi.org/10.3390/math7060509.

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Modern economics was born in the Marginal revolution and the Keynesian revolution. These revolutions led to the emergence of fundamental concepts and methods in economic theory, which allow the use of differential and integral calculus to describe economic phenomena, effects, and processes. At the present moment the new revolution, which can be called “Memory revolution”, is actually taking place in modern economics. This revolution is intended to “cure amnesia” of modern economic theory, which is caused by the use of differential and integral operators of integer orders. In economics, the description of economic processes should take into account that the behavior of economic agents may depend on the history of previous changes in economy. The main mathematical tool designed to “cure amnesia” in economics is fractional calculus that is a theory of integrals, derivatives, sums, and differences of non-integer orders. This paper contains a brief review of the history of applications of fractional calculus in modern mathematical economics and economic theory. The first stage of the Memory Revolution in economics is associated with the works published in 1966 and 1980 by Clive W. J. Granger, who received the Nobel Memorial Prize in Economic Sciences in 2003. We divide the history of the application of fractional calculus in economics into the following five stages of development (approaches): ARFIMA; fractional Brownian motion; econophysics; deterministic chaos; mathematical economics. The modern stage (mathematical economics) of the Memory revolution is intended to include in the modern economic theory new economic concepts and notions that allow us to take into account the presence of memory in economic processes. The current stage actually absorbs the Granger approach based on ARFIMA models that used only the Granger–Joyeux–Hosking fractional differencing and integrating, which really are the well-known Grunwald–Letnikov fractional differences. The modern stage can also absorb other approaches by formulation of new economic notions, concepts, effects, phenomena, and principles. Some comments on possible future directions for development of the fractional mathematical economics are proposed.
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26

Alferev, Dmitry. "Economics through the prism of mathematical structures." Artificial societies 17, no. 3 (2022): 0. http://dx.doi.org/10.18254/s207751800010809-8.

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Economics is a human science. But this does not mean that many mathematical tools do not work in it. This only determines that it has its own specifics, and this must be taken into account in the framework of mathematical modeling. Moreover, the humanitarian nature of economic disciplines cannot be the reason for the decisions made in it, based on someone else&apos;s authoritative subjective opinion. Mathematics in its nature allows you to make a really correct and reasonable choice. The article considers a wide range of classical mathematical tools of an economist, which has been developed throughout human history in solving various economic problems. The development of mathematical economics is also presented in accordance with the currently relevant machine learning and artificial intelligence algorithms and some other mathematical areas that can be applied to economic processes and phenomena.
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27

Düppe, Till. "Debreu's apologies for mathematical economics after 1983." Erasmus Journal for Philosophy and Economics 3, no. 1 (March 23, 2010): 1. http://dx.doi.org/10.23941/ejpe.v3i1.37.

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When reassessing the role of Debreu's axiomatic method in economics, one has to explain both its success and unpopularity; one has to explain the "bright shadow" Debreu cast on the discipline: sheltering, threatening, and difficult to pin down. Debreu himself did not expect to have such an influence. Before he received the Bank of Sweden Prize in 1983 he had never openly engaged with the methodology or politics of mathematical economics. When in several speeches he later rigorously distinguished mathematical form from economic content and claimed this as the virtue of mathematical economics, he did both: he defended mathematical reasoning against the theoretical innovations since the 1970s and expressed remorse for having promised too much because it cannot support claims about economic content. The analysis of this twofold role of Debreu's axiomatic method raises issues of the social and political responsibility of economists over and above standard epistemic issues.
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28

Makarov, Sergey I. "Mathematical modeling skills development among students of universities of economics." Samara Journal of Science 9, no. 2 (May 29, 2020): 254–57. http://dx.doi.org/10.17816/snv202307.

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This paper discusses approaches to economic and mathematical modeling skills development among students of universities of economics. The need for this competency among specialists in the digital economy is shown. The motivation of the student the future specialist in the digital economy in mastering the basic techniques of economic processes and systems modeling is outlined. The sections of the school course in mathematics are given, which are the basis for the development of these skills. Mathematical courses are examined; their study is considered to be the foundation for the development of the competence in economic processes modeling. The author describes the main types of mathematical models that are studied at the present stage at universities of economics and are widely used in the digital economy. The author also presents a classification of the models used in the educational process while studying mathematical courses. The main requirements for economic-mathematical models are discussed and substantiated. The author has listed necessary requirements for teachers of mathematical departments of universities. These requirements can help them to teach basic mathematics and its applied sections (e.g. mathematical modeling) to students successfully. The main conclusions and results of the study can be used in the practical work of teachers of mathematical departments at universities of economics when creating electronic teaching aids of economic and mathematical modeling and methods of their application in the educational process.
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29

Serbenyuk, Symon. "On Some Aspects of the Examination in Econometrics." Journal of Vasyl Stefanyk Precarpathian National University 8, no. 3 (November 3, 2021): 7–16. http://dx.doi.org/10.15330/jpnu.8.3.7-16.

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Teaching econometrics has been studied by a number of researchers, however, there is little information available on the quality of examination and on simplification of tests for demonstration the high-quality knowledge by students in concrete topics of econometrics or mathematical economics.One can note the following main goals of studying the basics of mathematical economics or econometrics by students: forming the notions of mathematical model and of modeling economic processes and phenomena; understanding a role of using mathematical models for economics research and obtaining scientific results; formatting skills for constructing mathematical models in economics, for solving economics problems by mathematical modeling.The main goal of this paper is to simplify test tasks, is to help to students to demonstrate the high-quality knowledge in certain areas of mathematical economics, and also is to construct a system of testing tasks, in which the emphasis was placed on the knowledge and understanding of an algorithm of solving the problem.In the present paper, to quality examine the student knowledge in the basics of mathematical economics, a certain system of tests was constructed and is considered. The main attention is also given to algorithms and techniques of solving some tasks (problems) of mathematical economics. The following topics of mathematical economics are viewed: constructing mathematical models of linear programming, the input-output model, the Monge-Kantorovich transportation problem, the simplex method of linear programming, the graphic method of linear and nonlinear programming, the method of Lagrange multipliers in mathematical optimization. Some primary basic results of studying linear programming, nonlinear programming, and the input-output model are noted.A new system of tests that satisfies the aim of this paper is modeled. The described tests require less time for solving than usual tasks. Here we do not focus on the repetition of auxiliary mathematical knowledge and arithmetic skills. These tests are simplified versions of standard tasks and help students to demonstrate knowledge in the mentioned topics of mathematical economics. The tasks are focused only on the knowledge of basic formulas, techniques, and connections between mathematical objects, economic systems, and their elements.
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30

Upadhyaya, Yadav Mani. "Economics and Mathematical Relationship: A Case Study in University Economics Course of Nepal." Interdisciplinary Journal of Management and Social Sciences 2, no. 2 (December 31, 2021): 125–36. http://dx.doi.org/10.3126/ijmss.v2i2.42609.

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In our teaching program and methods, the mathematical approach has a major influence on economics. In this paper, I examined the aforementioned economics and mathematical relationships, taking into account their historical development as well as the experience gained over several years in the Masters in Economics Sciences' economics course. Changes in the initial practices in the classroom entering university have prompted a rethinking of a number of fundamental questions, including: What parameters should be used to determine the most suitable curriculum and teaching approach in a changing environment? What mathematical singularities does economics teaching present? This last question introduces us to the topic we'll be discussing. How much math should be taught in economics classes? Is it important for students to have a strong mathematical foundation before they study economics? For some teachers, economic issues are merely an addendum to the practical portion of the topic, while for others; economic models are the subject's main focus. As a consequence, mathematics in general is now assisting in the analysis of economics. In conclusion, as students study economics, it becomes more difficult for them to study other mathematics topics. Since not all students excel at math, economics is a more difficult subject to study. However, studying algebra, calculus, and logarithms, among other subjects, makes economics more important.
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31

Golland, Louise Ahrndt. "Formalism in Economics." Journal of the History of Economic Thought 18, no. 1 (1996): 1–12. http://dx.doi.org/10.1017/s1053837200002935.

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The transformation of economics through its mathematization has been of interest to historians of economics and economic thought. While considering aspects of this history, Philip Mirowski (1986a, 1992) and Lionel Punzo (1989, 1991) have introduced David Hilbert's work, the Hilbert program, formalism, and Kurt GddePs results into their discussions in a way that is inconsistent with the mathematical community's understanding of mathematical history.
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32

Sihag, Balbir S. "Exploring the Origin of Mathematical Economics." Theoretical Economics Letters 06, no. 01 (2016): 87–96. http://dx.doi.org/10.4236/tel.2016.61011.

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33

Beardon, A. F. "Analaysis and topology in mathematical Economics." Irish Mathematical Society Bulletin 0033 (1994): 10–21. http://dx.doi.org/10.33232/bims.0033.10.21.

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34

LeeChaiOn. "Historical Materialism and Marxian Mathematical Economics." MARXISM 21 14, no. 1 (February 2017): 233–43. http://dx.doi.org/10.26587/marx.14.1.201702.008.

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35

Balls, Kim G., and Ron C. Mittelhammer. "Mathematical Statistics for Economics and Business." Journal of the American Statistical Association 92, no. 437 (March 1997): 386. http://dx.doi.org/10.2307/2291489.

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36

Caldwell, Bruce, and E. Roy Weintraub. "How Economics Became a Mathematical Science." Southern Economic Journal 69, no. 4 (April 2003): 1011. http://dx.doi.org/10.2307/1061666.

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37

Coyle, Diane. "HOW ECONOMICS BECAME A MATHEMATICAL SCIENCE." Economic Affairs 23, no. 2 (June 2003): 61. http://dx.doi.org/10.1111/1468-0270.00421_7.

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38

Levin, Vitaly I. "Continuous-Logical Methods in Mathematical Economics." Studia Humana 5, no. 1 (March 1, 2016): 31–39. http://dx.doi.org/10.1515/sh-2016-0003.

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Abstract An application of continuous logic for the mathematical description of economical systems is given. Parallel, sequential, parallel-sequential and sequentialparallel systems are calculated using continuous logic (CL) methods.
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39

Khan, M. A. "How Economics Became a Mathematical Science." History of Political Economy 36, no. 1 (March 1, 2004): 212–14. http://dx.doi.org/10.1215/00182702-36-1-212.

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40

Porter, Theodore M. "Interpreting the Triumph of Mathematical Economics." History of Political Economy 25, suppl_1 (January 1, 1993): 54–68. http://dx.doi.org/10.1215/00182702-1993-suppl_1012.

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41

Israel, Giorgio. "How Economics Became a Mathematical Science." Economic Journal 114, no. 496 (May 27, 2004): F369—F370. http://dx.doi.org/10.1111/j.1468-0297.2004.00226_20.x.

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42

HENDERSON, JAMES P. "EDWARD ROGERS'S CONTRIBUTIONS TO MATHEMATICAL ECONOMICS." Manchester School 59, no. 3 (September 1991): 257–73. http://dx.doi.org/10.1111/j.1467-9957.1991.tb00450.x.

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43

ROSSER, J. BARKLEY. "ON THE FOUNDATIONS OF MATHEMATICAL ECONOMICS." New Mathematics and Natural Computation 08, no. 01 (March 2012): 53–72. http://dx.doi.org/10.1142/s1793005712400029.

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Kumaraswamy Vela Velupillai74 presents a constructivist perspective on the foundations of mathematical economics, praising the views of Feynman in developing path integrals and Dirac in developing the delta function. He sees their approach as consistent with the Bishop constructive mathematics and considers its view on the Bolzano-Weierstrass, Hahn-Banach, and intermediate value theorems, and then the implications of these arguments for such "crown jewels" of mathematical economics as the existence of general equilibrium and the second welfare theorem. He also relates these ideas to the weakening of certain assumptions to allow for more general results as shown by Rosser51 in his extension of Gödel's incompleteness theorem in his opening section. This paper considers these arguments in reverse order, moving from the matters of economics applications to the broader issue of constructivist mathematics, concluding by considering the views of Rosser on these matters, drawing both on his writings and on personal conversations with him.
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44

Sofronidis, Nikolaos Efstathiou. "Mathematical Economics and Descriptive Set Theory." Journal of Mathematical Analysis and Applications 264, no. 1 (December 2001): 182–205. http://dx.doi.org/10.1006/jmaa.2001.7669.

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45

Gallardo Pérez, Henry de Jesús, and Mawency Vergel Ortega. "Mathematical economics in the explanation of economic growth in economies with endogenous and exogenous technological change." Revista Boletín Redipe 10, no. 5 (May 1, 2021): 101–9. http://dx.doi.org/10.36260/rbr.v10i5.1287.

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Economic growth is a function of the interactions between the different productive factors framed in the economic policy of an economy, in particular, it can be expressed in terms of labour force, productive resources (land, capital) and technology, among others. The present work pretends to approximate a model to explain the economic growth in developing economies, for which a model is proposed that explains this growth in function of the referred factors; then production is proposed in function of capital and work and two models are adjusted, one with exogenous technological change and the other that involves technological change in an endogenous manner. The model is developed with a production function with constant substitution elasticity so that it is applicable to both developed and developing economies, since it is to be expected that in developed economies the substitution elasticity is unitary, which would lead to a Cobb-Douglas-type production function, but it is very probable that in incipient economies the function with constant substitution elasticity better reflects the relationship between production factors and economic growth. The research allows the development of the corresponding mathematical model in each case, the economic and mathematical foundations of each model are presented and validated according to economic theories. The behaviour of variables such as savings, investment, income, consumption, capital and their relationships in each model is analysed.
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46

Meilani, Reka. "MATEMATIKA DALAM KEUANGAN SYARIAH." Budgeting: Jurnal Akuntansi Syariah 3, no. 2 (November 24, 2022): 115–30. http://dx.doi.org/10.32923/bdg.v3i2.2846.

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Mathematical modeling plays a major role in various disciplines. The contribution of mathematical modeling is not only attached to the concepts of general sciences, such as conventional economics and finance, but also includes Islamic sciences, such as Islamic economics and finance. This study aims to reveal the role of mathematics in the development of Islamic economics and finance. This study uses a qualitative approach in the form of library research. The results of the discussion are expressed through the ideas described in two general information, namely: (1) The results of the analysis of mapping studies on mathematical models in Islamic economics and finance, and (2) an explanation of several examples of mathematical models applied in economic theories and Islamic finance. From the results of this study, it was found that the number of publications on the development of mathematical models in Islamic economics and finance research from 1980-2020 experienced a significant increase and also began to have a high impact on other research. In addition, the development of mathematical models in solving Islamic economic and financial problems is also a trend in current research. An example is research on the development of mathematical models on the concept of profit-sharing financing and the concept of zakat.
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47

Papageorgiou, Nikolaos S. "On transition multimeasures with values in a Banach space." Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics 49, no. 1 (August 1990): 72–89. http://dx.doi.org/10.1017/s1446788700030251.

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The theory of multimeasures (set valued measures), has its origins in mathematical economics and in particular in equilibrium theory for exchange economies with production, in which the coalitions and not the individual agents are the basic economic units (see Vind [25] and Hildenbrand [15]). Since then the subject of multimeasures has been developed extensively. Important contributions were made, among others, by Artstein [1], Costé [8], [9], Costé and Pallu de la Barrière [10], Drewnowski [12], Godet-Thobie [13], Hiai [14] and Pallu de la Barrière [17]. Further applications in mathematical economics can be found in Klein and Thompson [16] and Papageorgiou [19].
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48

Charles, Loïc, and Christine Théré. "CHARLES RICHARD DE BUTRÉ: PIONEER OF MATHEMATICAL ECONOMICS." Journal of the History of Economic Thought 38, no. 3 (August 15, 2016): 311–27. http://dx.doi.org/10.1017/s1053837216000353.

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Historians of economics have acknowledged the significant role François Quesnay and the Physiocrats played in the early development of mathematical economics. It is, however, important to note that although the Tableau économique could well be translated into algebra, Quesnay never did it. As part of our research on Charles Richard de Butré, an obscure collaborator of François Quesnay, we have uncovered documents that show that he was one Physiocrat who did use algebra to explain his theoretical conceptions. In two texts written at the end of 1766 and the beginning of 1767, Butré systematically used algebra as an aid for economic reasoning. Our argument is that these texts provide very interesting insights into the development of early mathematical economics.
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49

Muyo Yildirim, Munevver, and Luan Vardari. "Mathematical and financial literacy." Cypriot Journal of Educational Sciences 15, no. 6 (December 31, 2020): 1574–86. http://dx.doi.org/10.18844/cjes.v15i6.5318.

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This study aimed to determine the financial and mathematical literacy levels of university students. Therfore the study contributes to the reflection of students’ knowledge of mathematics and finane aquired during their studies to the problems they face in real life as well as to examine how this bacground affect their opinions in practice. Findings has shown that students' financial and mathematics literacy general achievement levels is 39.7%. It is satisfactory to found that the studnets of Faculty of Economics have higher levels of financial mathematical literacy knowledge than those of the Faculty of Education and the Faculty of Technology, and that the Faculty of Education is at the forefront of the Faculty of Technology studentsdespite the fact that the Faculty of Education does not proviede does not courses in the field of economics and finance. In addition, considering the university students to be more sensitive about their current financial and economic information, it is not expected that the overall success in the findings will be lower than 40%. Keywords: Mathematical Literacy, Financial Literacy, Prizren University, Students, Kosovo;
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50

Khamkhoeva, F., and Z. Khautieva. "MODERN PROBLEMS OF APPLYING MATHEMATICAL METHODS IN THE ASPECT OF ECONOMICS." National Association of Scientists 3, no. 74 (December 30, 2021): 69–72. http://dx.doi.org/10.31618/nas.2413-5291.2021.3.74.530.

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The penetration of the mathematical apparatus into the economy created the basis for the development of methods of economic analysis, econometrics, mathematical programming, economic statistics, etc. Today, the interpenetration of different branches of knowledge continues, in particular, the application of mathematical methods in the natural and social sciences and in the economic sphere. Among mathematical methods of data processing are polynomial, linear, quadratic, trigonometric, exponential and combined dependencies, differential and algebraic equations. The statistical processing of data from the evaluation of the structure and dynamics of the phenomenon has gone in the direction of correlation analysis and forecasting. The deep penetration of mathematics into specific sciences and the success achieved through a combination of methods from different branches of knowledge is described by many researchers. The possibilities of applying mathematics are increasingly being explored in areas of knowledge where phenomena are poorly structured and characterized by the high complexity of sociology, political science, management and economics. The article presents a retrospective analysis of the development of scientific and applied research concerning the process of mathematics of science and the possibilities of using mathematical methods in economics in particular. Problems and constraints encountered in applying mathematical methods in economic research have been identified. Measures have been identified to ensure the adequacy of the development of economic and mathematical models from the standpoint of approaches to their construction, the improvement of management processes and the improvement of the training of specialists in economic fields.
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